Infilling, climatology and anomalies. For some reason Steven Goddard has gone viral, and has been on some right wing media. Judith Curry gives a summary, with links. WUWT has had a varied role. Zeke has continued at Lucia's. I chipped in too. Then it took an odd turn. Anthony got invested in disputing SG's claims, only moderately exaggerated, about the number of USCHN stations that actually reported each month.
When he found that there were quite a lot, "zombie" stations became the enemy. And with that, infilling. That can be done, but needs care unlike here. USHCN does it by ensuring that every month has an entry for each of its stations, which ideally never change. But in fact some do become defunct. So that is the latest villainy. But there is nothing wrong with the infilling method.
I've been arguing in many forums that the US average, for a month say, is a spatial integral, and they are doing numerical integration. Numerical integration formulae are usually based on integrating an interpolation formula. If you first interpolate extra points using that formula, it makes no difference. Any other good formula will also do. I don't have many wins. So I thought I would give a simple and fairly familiar example which would show the roles of averaging, climatology, infilling and anomalies.
It's the task of calculating an average for one year for one station. Since it's been in the news, and seems to be generally a good station, I chose Luling, Texas. From comments, I see that I should emphasise that I'm not, in this example, trying to calculate the temperature of the US, or any kind of trend.
The issue is very simple. Given a temp record of this one place, and the monthly averages with a missing , what can be said about the annual average for for that place. Update: I have a new post with a graphics version here To simplify, I'll round numbers, assume months of equal length. Climatology for each month will be simply the average of all instances, and the anomaly is just the difference from that.
